cum_sum:
    description: |
        Computes the cumulative sum of input tensor along axis.

        .. math::
        
            y_i = x_1 + x_2 + x_3 + ... + x_i
    
        Args:
            exclusive (bool): By default, this op performs an inclusive cumsum, which means that the first
                element of the input is identical to the first element of the output. Default: ``False`` .
            reverse (bool): If ``True`` , perform inverse cumulative sum. Default: ``False`` .
    
        Inputs:
            - **input** (Tensor) - The input Tensor with shape
              :math:`(N, *)` where :math:`*` means any number of additional dimensions.
            - **axis**  (int) - The axis to accumulate the tensor's value. Only constant value is allowed.
              Must be in the range [-rank(input), rank(input)).
    
        Outputs:
            Tensor, the shape of the output tensor is consistent with the input tensor's.
    
        Raises:
            TypeError: If `exclusive` or `reverse` is not a bool.
            TypeError: If `axis` is not an int.
    
        Supported Platforms:
            ``Ascend`` ``GPU`` ``CPU``
    
        Examples:
            >>> import numpy as np
            >>> from mindspore import Tensor, ops
            >>> x = Tensor(np.array([[3, 4, 6, 10], [1, 6, 7, 9], [4, 3, 8, 7], [1, 3, 7, 9]]).astype(np.float32))
            >>> cumsum = ops.CumSum()
            >>> # case 1: along the axis 0
            >>> y = cumsum(x, 0)
            >>> print(y)
            [[ 3.  4.  6. 10.]
             [ 4. 10. 13. 19.]
             [ 8. 13. 21. 26.]
             [ 9. 16. 28. 35.]]
            >>> # case 2: along the axis 1
            >>> y = cumsum(x, 1)
            >>> print(y)
            [[ 3.  7. 13. 23.]
             [ 1.  7. 14. 23.]
             [ 4.  7. 15. 22.]
             [ 1.  4. 11. 20.]]
            >>> # Next demonstrate exclusive and reverse, along axis 1
            >>> # case 3: exclusive = True
            >>> cumsum = ops.CumSum(exclusive=True)
            >>> y = cumsum(x, 1)
            >>> print(y)
            [[ 0.  3.  7. 13.]
             [ 0.  1.  7. 14.]
             [ 0.  4.  7. 15.]
             [ 0.  1.  4. 11.]]
            >>> # case 4: reverse = True
            >>> cumsum = ops.CumSum(reverse=True)
            >>> y = cumsum(x, 1)
            >>> print(y)
            [[23. 20. 16. 10.]
             [23. 22. 16.  9.]
             [22. 18. 15.  7.]
             [20. 19. 16.  9.]]